Groq vs MiniMax: Token Pricing, Speed & Intelligence
Full comparison of Groq and MiniMax — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Groq
LPU-powered inference — the fastest tokens per second available
Groq runs custom Language Processing Units (LPUs) that deliver dramatically higher throughput than GPU-based inference — Llama 3.3 70B reaches 750+ tokens/second on Groq, versus 100–200 on typical GPU providers. Ideal for latency-sensitive applications, real-time chat, and high-volume batch workloads.
MiniMax
Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
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Live token pricing
Strengths & weaknesses
Groq
MiniMax
Key differentiators
Frequently asked questions
Groq FAQs
How fast is Groq inference?
Groq delivers 750+ tokens/second on Llama 3.3 70B and 1,200+ tokens/second on Llama 3.1 8B. This is 4–5× faster than typical GPU-based providers, making it ideal for real-time applications.
How much does Groq cost?
Llama 3.3 70B costs $0.59/1M input and $0.79/1M output tokens. Llama 3.1 8B is just $0.05/$0.08 per 1M tokens — among the cheapest options for a capable open-weight model.
What is a Groq LPU?
A Language Processing Unit (LPU) is Groq's custom silicon designed specifically for sequential token generation. Unlike GPUs which are optimised for parallel matrix operations, LPUs excel at the autoregressive decoding step that dominates LLM inference latency.
MiniMax FAQs
What is MiniMax M2.7?
MiniMax M2.7 is MiniMax's latest chat model, supporting a 205K token context window. It is designed for enterprise chat, long-document analysis, and agentic tasks.
Is MiniMax available internationally?
Yes. The MiniMax API is accessible globally, and models are also available through OpenRouter and other inference aggregators.
Provider resources
Groq — LPU-powered inference — the fastest tokens per second available
Groq runs custom Language Processing Units (LPUs) that deliver dramatically higher throughput than GPU-based inference — Llama 3.3 70B reaches 750+ tokens/second on Groq, versus 100–200 on typical GPU providers. Ideal for latency-sensitive applications, real-time chat, and high-volume batch workloads.
Groq's custom LPU chips deliver 750+ tokens/sec on Llama 3.3 70B — 4–5× faster than any GPU-based provider.
MiniMax — Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.
Key strengths compared
Groq
- ▸750+ tokens/sec on Llama 3.3 70B — fastest GPU-class inference
- ▸Sub-100ms time-to-first-token for real-time applications
- ▸Very competitive pricing on open-weight models
MiniMax
- ▸1M token context window
- ▸Competitive pricing
- ▸Strong multilingual performance
Provider category context
Groq is a inference api, founded in 2016. MiniMax is a frontier lab, founded in 2021. Groq as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. MiniMax as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose Groq if you need 750+ tokens/sec on llama 3.3 70b — fastest gpu-class inference. Choose MiniMax if you need 1m token context window. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.